This method involves determining settling velocities from SVI values through the use of statistical correlations. Because the SVI test is both easier to perform than the interfacial settling velocity test and is typically measured anyway, SVI is a powerful time-saving method with which to create flux curves.

TheoryGarrett, et al (1982) have shown that mathematical relationships with high confidence levels can be constructed between sludge settling velocity and the floc volume, Vf. The floc volume is equal to:

The floc volume is therefore in units of percent. to convert concentration in mg/l to g/100 ml, divide by 10,000.

Analysis

To create settling flux curves from this information, the operator must develop a correlation between solids settling velocity and SVI (floc volume). A representative cross section of operating solids concentrations should be used to ensure applicability of the model-to-system performance. It is recommended that the dilutions given in section 5.1.2 be used as a start. Determine SVI values for each of the dilutions, in ml/gm, and multiply by the associated concentration, in gm/100 ml, to get the respective floc volume.

Method 1 should be used to calculate settling velocities. The resulting data pairs should then be plotted, with settling velocity (in ft/day) on the y-axis. The Correlation Plot option in Graph Pac is ideally suited for this type of analysis. The settling velocity can be defined as a parameter. Floc volume can be defined as a parameter or as a calculated variable if variables are already defined for SVI in ml/g and MLSS in mg/l. The calculated floc volume is then:

Vf = (SVI*MLSS)/10,000.

Enter the settling velocity, SVI and MLSS values for dates not yet used in the database (the values can be erased once the correlation is calculated). Develop the correlation plot, and determine if any of the relationships have a high enough coefficient of correlation to warrant use. You may find it necessary to develop separate correlation plots between settling velocity and Vf for high and low MLSS concentrations. This procedure requires set up of three standard entered parameters (SVI, vs, associated MLSS values) and two calculated variables (Vf, C).

Once a satisfactory correlation has been developed, flux curves can be created from MLSS and SVI measurements. Convert the SVI value to a floc volume, and then calculate a settling velocity with the correlation plot.

The resulting settling velocities (in ft/hr) can then be entered, along with their associated concentration (in mg/l), into the Add New Flux Curves option discussed in Chapter Seven so that a new flux curve can be determined. For a better understanding of this procedure, read through the example below showing the mathematical correlation between settling velocity and floc volume.

ExampleGarret, et all (1982) developed a relationship between floc volume and settling velocity using data from four wastewater treatment facilities. They found that two relationships existed between floc volume and settling velocity, depending on the value of the floc volume. For a floc volume less than 40 percent, vs = 2.62*((100 - Vf)/100)3.83 Vf < 40%

RecommendationAlthough this method requires less time and effort than the direct measurement of settling velocities, the results are only as good as the correlation developed. The correlation is good only so long as the settling characteristics on which it was developed remain constant. A comparison of the two methods with respect to the prediction of clarifier performance should be performed, using the same sludge, to evaluate the efficacy of the correlation before it is given general application.FrequencyThe frequency of analysis required to ensure that the current settling flux curve is valid for the prevailing conditions is not a set period. Solids settling characteristics are sit-specific and can change due to temperature, organic loading (quantity and type), microbiological population dynamics and process modifications. These fluctuations mean that the determination of new flux curves cannot be set to a fixed schedule, in case process disturbances occur. Nonetheless, it is good practice to maintain a regular schedule of settling curve analyses, either direct measurements or from an SVI correlation, to determine if settling characteristics are changing over time, and if these changes can be anticipated. Experience is the best guide in the determination of when a new settling curve must be generated.